• Ensure that the appropriate telemetry in all public and private clouds is appropriate to meet cybersecurity use cases. • Ensure that the appropriate data normalization, aggregation, and context is provided to meet cybersecurity detection, threat hunt, incident response, governance, and compliance functions. • Knowledge about log collection and routing for AWS and Azure cloud environments, including data plane and control plane logs and ability to design data logging and routing architectures.

Role Description Cardinal Technology Systems Corp. is currently seeking a Jr. Data Analytics Engineer to work for our company. - Must possess DoD Top Secret, DHS EOD, CBP Full BI, or IT-I security clearance or have a current Single Scope Background Investigation (SSBI). (Basic Federal Clearance requirements are U.S. Citizenship, clear criminal history check, no recent or pending bankruptcies) - Assist in the design, development, and deployment of reports, dashboards, and data visualizations using business intelligence (BI) tools such as SAP Business Objects or similar platforms. - Collaborate with data engineering teams to support the use of dimensional models, including fact and dimension tables (star/snowflake schemas), for reporting. - Write and maintain SQL queries within Oracle and Databricks environments to extract and prepare data for reporting applications. - Work with business analysts and stakeholders to help gather requirements, translate business needs into technical specifications, and support the delivery of reporting solutions. - Assist in monitoring and improving the performance of reports and underlying queries to help ensure a reliable and user-friendly experience. - Gain exposure to and support the use of AWS services (e.g., S3, EMR, Redshift, Glue) for cloud-based reporting solutions. - Support the management of reporting assets, including documentation, version control, scheduled refreshes, and ongoing maintenance and enhancements. Qualifications - Bachelor's degree in computer science or related engineering field. - 1-3 (maximum of 5 years) of hands-on experience with SQL programming. - 1-3 (maximum of 5 years) of experience with at least one major BI platform (e.g. PowerBI, Tableau, Qlik). - Experience with performing data analysis and interpreting results. - Conceptual understanding of data warehousing concepts and dimensional modeling, including a clear ability to articulate the difference and use cases for star vs. snowflake schemas. - High level of self-motivation, willingness to learn new technologies and work in a distributed team environment. - The person in this position needs to occasionally move about inside the office to access file cabinets, office machinery, or to communicate with co-workers, management, and customers, which may involve delivering presentations. Requirements - Must possess DoD Top Secret, DHS EOD, CBP Full BI, or IT-I security clearance or have a current Single Scope Background Investigation (SSBI). (Basic Federal Clearance requirements are U.S. Citizenship, clear criminal history check, no recent or pending bankruptcies) Preferences - 1-3 years of experience in dedicated reporting, business intelligence, or data analytics role. - Experience developing reports and running queries within a Databricks environment (using notebooks, SQL Warehouses, etc.). - Familiarity with navigating the AWS ecosystem, specifically with services related to data storage and access like S3 and IAM. - AWS Certification (e.g. AWS Certified Data Analytics – Specialty or Solutions Architect). - Proficiency in a scripting language, particularly Python (Pandas, Pyspark) for data manipulation or automation. - Strong communication skills with ability to present technical findings to non-technical stakeholders. Benefits - Medical, Dental, Vision Benefits - Paid Life - Paid Vacation, Holidays, Sick Leave, Floating Holidays, Bereavement Leave - Semi-monthly pay cycle

Title: Lead Data Engineer Location: Illinois Job Description: Posting Type Hybrid Job Overview Relativity powers the world’s most critical legal, compliance, and investigative work. From corporate compliance to human rights, our platform must preserve trust in global investigations while handling petabytes of sensitive evidence. Our team builds the distributed data backbone that powers AI-assisted evidence analysis across billions of documents daily. We are at the forefront of Legal Data Intelligence, building technology that helps organizations Organize Data, Discover Truth, and Act on It. As a Lead Data Engineer, you are the technical leader for your team: hands-on, design focused, and accountable for elevating engineering quality. You’ll drive architectural decisions, guide how systems are built, and mentor others to deliver high-performance, cloud-native data systems. You will work across modern data tooling, including Databricks, Kafka, dbt, and Snowflake, to directly support some of the most mission critical legal processes worldwide. Job Description and Requirements What You’ll Do • Architect, build, and operate distributed data pipelines and services that process massive volumes of structured and unstructured data. • Design and deliver scalable, secure, and observable data integration and ETL solutions using dbt to ensure end-to-end data integrity and availability. • Partner with AI/ML engineers and data scientists to build data foundations that accelerate model training, experimentation, and production deployment. • Drive improvements in data quality, lineage, reliability, and SLAs, shaping engineering standards for your team. • Contribute reusable patterns, frameworks, and best practices that strengthen our Azure cloud-native data platform. What You’ll Bring • 6+ years of experience in data engineering, backend engineering, or data architecture with substantial work on distributed systems and cloud-first data platforms. • Deep understanding of data modeling, ETL/ELT design, and workflow orchestration. • Proven ability to lead technical decisions within a team—breaking down complex problems, defining trade-offs, and driving alignment. • Strong communication skills and the ability to explain complex data concepts to diverse audiences. • A commitment to building systems that create clarity and insight through data, not just moving data from point A to point B. Preferred Experience • Expertise with Databricks and/or Azure-based data architectures. • Background building systems that support ML workflows or AI-driven applications. • Experience leading modernization or migration of large-scale data platforms. • Strong understanding of observability and cost-optimization strategies for cloudbased data systems. Relativity is committed to competitive, fair, and equitable compensation practices. This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives. The expected salary range for this role is between following values: $150,000 and $224,000 The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position. Required Skills: Documentations, Innovation, Leadership, Problem Solving, Process Improvements, Project Management, Quality Assurance (QA), Risk Management, Technical Knowledge, Troubleshooting

Cargill's size and scale allows us to make a positive impact in the world. Our purpose is to nourish the world in a safe, responsible and sustainable way. We are a family company providing food, ingredients, agricultural solutions and industrial products that are vital for living. We connect farmers with markets so they can prosper. We connect customers with ingredients so they can make meals people love. And we connect families with daily essentials - from eggs to edible oils, salt to skincare, feed to alternative fuel. Our 160,000 colleagues, operating in 70 countries, make essential products that touch billions of lives each day. Join us and reach your higher purpose at Cargill. Job Purpose and Impact - The Professional, Data Engineering job designs, builds and maintains moderately complex data systems that enable data analysis and reporting. With limited supervision, this job collaborates to ensure that large sets of data are efficiently processed and made accessible for decision making. Key Accountabilities - DATA & ANALYTICAL SOLUTIONS: Develops moderately complex data products and solutions using advanced data engineering and cloud based technologies, ensuring they are designed and built to be scalable, sustainable and robust. - DATA PIPELINES: Maintains and supports the development of streaming and batch data pipelines that facilitate the seamless ingestion of data from various data sources, transform the data into information and move to data stores like data lake, data warehouse and others. - DATA SYSTEMS: Reviews existing data systems and architectures to implement the identified areas for improvement and optimization. - DATA INFRASTRUCTURE: Helps prepare data infrastructure to support the efficient storage and retrieval of data. - DATA FORMATS: Implements appropriate data formats to improve data usability and accessibility across the organization. - STAKEHOLDER MANAGEMENT: Partners with multi-functional data and advanced analytic teams to collect requirements and ensure that data solutions meet the functional and non-functional needs of various partners. - DATA FRAMEWORKS: Builds moderately complex prototypes to test new concepts and implements data engineering frameworks and architectures to support the improvement of data processing capabilities and advanced analytics initiatives. - AUTOMATED DEPLOYMENT PIPELINES: Implements automated deployment pipelines to support improving efficiency of code deployments with fit for purpose governance. - DATA MODELING: Performs moderately complex data modeling aligned with the datastore technology to ensure sustainable performance and accessibility. Qualifications - Minimum requirement of 2 years of relevant work experience. Typically reflects 3 years or more of relevant experience. Preferred Qualifications: - Experience with corporate-level data storage and processing platforms (AWS, Snowflake, etc.) - Proven history in design, development, and maintenance of scalable ETL pipelines for multi-scale datasets - Proven experience in business partnership, requirements gathering, and agile execution in large-scale data development programs Cargill is an equal opportunity employer and committed to providing accommodation to our job applicants with disabilities.